Tools and Methods for Real-World Evidence Generation: Pragmatic Trials, Electronic Consent, and Data Linkages

Digital consent in gynecology: an evaluation of patient experience

INTRODUCTION

The surgical consent process is a crucial discussion between patient and surgeon, which is predominantly documented utilizing hand-written forms. The exchange of individualized information allows the patient to make a truly informed decision. Digital consent (also known as electronic consent or e-consent) has been shown to improve accuracy of information provided without increasing the time taken to consent patients. We aimed to evaluate patient experience and effectiveness of digital consent in a gynecology department in a tertiary London Teaching Hospital.

METHODS

A questionnaire was designed and completed by 100 patients undergoing gynecological surgery: 50 consented using paper and 50 consented digitally. The questionnaire included 8 statements, with five possible answers to select, ranging from strongly agree to strongly disagree, on a standard five-point Likert Scale. Patients were all female and categorized into age groups (deciles) and asked whether consent was taken digitally or on paper. Data were collected between January and July 2021.

RESULTS

Most responses were positive with 87% (694/800) of responses to the questions being either strongly agree or agree. Patients who were consented using paper selected 'strongly agree' 43.5% (174/400) of the time in comparison to 64.8% (259/400) of the time when they were consented digitally. The majority, 86% (43/50), of digitally consented patients received a copy of the consent form in comparison to 18% (9/50) of those consented using paper. On average, the patients consented digitally were older than their paper-consented counterparts (49-58 and 59-68 respectively). The mean scores for the questions relating to the ease of reading the form, ease of understanding the form, understanding of the potential complications, and overall satisfaction were higher in those digitally consented (p < 0.05).

DISCUSSION

Overall, patients were satisfied with both methods of consent. However, individuals who were consented digitally reported higher levels of satisfaction throughout the consent process, compared to paper consent. These data suggest that digital consent is an acceptable alternative to paper consent for patients and facilitates adherence to national consent guidance, which stipulates patients should be given the information they request.

Advancing rapid adaptation for urgent public health crises: Using implementation science to facilitate effective and efficient responses

Responding rapidly to emerging public health crises is vital to reducing their escalation, spread, and impact on population health. These responses, however, are challenging and disparate processes for researchers and practitioners. Researchers often develop new interventions that take significant time and resources, with little exportability. In contrast, community-serving systems are often poorly equipped to properly adopt new interventions or adapt existing ones in a data-driven way during crises' onset and escalation. This results in significant delays in deploying evidence-based interventions (EBIs) with notable public health consequences. This prolonged timeline for EBI development and implementation results in significant morbidity and mortality that is costly and preventable. As public health emergencies have demonstrated (e.g., COVID-19 pandemic), the negative consequences often exacerbate existing health disparities. Implementation science has the potential to bridge the extant gap between research and practice, and enhance equity in rapid public health responses, but is underutilized. For the field to have a greater "real-world" impact, it needs to be more rapid, iterative, participatory, and work within the timeframes of community-serving systems. This paper focuses on rapid adaptation as a developing implementation science area to facilitate system responses during public health crises. We highlight frameworks to guide rapid adaptation for optimizing existing EBIs when responding to urgent public health issues. We also explore the economic implications of rapid adaptation. Resource limitations are frequently a central reason for implementation failure; thus, we consider the economic impacts of rapid adaptation. Finally, we provide examples and propose directions for future research and application.

Evolving a national clinical trials learning health system

Clinical trials generate key evidence to inform decision making, and also benefit participants directly. However, clinical trials frequently fail, often struggle to enroll participants, and are expensive. Part of the problem with trial conduct may be the disconnected nature of clinical trials, preventing rapid data sharing, generation of insights and targeted improvement interventions, and identification of knowledge gaps. In other areas of healthcare, a learning health system (LHS) has been proposed as a model to facilitate continuous learning and improvement. We propose that an LHS approach could greatly benefit clinical trials, allowing for continuous improvements to trial conduct and efficiency. A robust trial data sharing system, continuous analysis of trial enrollment and other success metrics, and development of targeted trial improvement interventions are potentially key components of a Trials LHS reflecting the learning cycle and allowing for continuous trial improvement. Through the development and use of a Trials LHS, clinical trials could be treated as a system, producing benefits to patients, advancing care, and decreasing costs for stakeholders.

Real-world studies: bridging the gap between trial-assessed efficacy and routine care

Even though randomized controlled clinical trials (RCTs) have been accepted as the gold standard for official assessment of novel interventions, there is a substantial gap between the efficacy observed in RCTs and the impact on clinical practice and in terms of patient benefit. While real-world studies (RWS) are emerging to confer valuable complementing evidence in this regard and beyond, the evolving role of RWS is yet to be agreed. This article delineates an updated profile of RWS covering effectiveness verification, rare adverse effects discovery, indication repurposing, to name a few. RWS tends not only to improve the efficiency of clinical investigations for regulatory approval, but also optimizes the whole-life cycle evaluation of biomedical/pharmaceutical products.

Understanding innovation of health technology assessment methods: the IHTAM framework

Adequate methods are urgently needed to guarantee the good practice of health technology assessment (HTA) for technologies with novel properties. The aim of the study was to construct a conceptual framework to help understand the innovation of HTA methods (IHTAM). The construction of the IHTAM framework was based on two scoping reviews, one on the current practice of innovating methods, that is existing HTA frameworks, and one on theoretical foundations for innovating methods outside the HTA discipline. Both aimed to identify and synthesize concepts of innovation (i.e., innovation processes and roles of stakeholders in innovation). Using these concepts, the framework was developed in iterative brainstorming sessions and subsequent discussions with representatives from various stakeholder groups. The framework was constructed based on twenty documents on innovating HTA frameworks and fourteen guidelines from three scientific disciplines. It includes a generic innovation process consisting of three phases (“Identification,” “Development,” and “Implementation”) and nine subphases. In the framework, three roles that HTA stakeholders can play in innovation (“Developers,” “Practitioners,” and “Beneficiaries”) are defined, and a process on how the stakeholders innovate HTA methods is included. The IHTAM framework visualizes systematically which elements and stakeholders are important to the development and implementation of novel HTA methods. The framework could be used by all stakeholders involved in HTA innovation to learn how to engage dynamically and collaborate effectively throughout the innovation process. HTA stakeholders in practice have welcomed the framework, though additional testing of its applicability and acceptance is essential.

Incidence and Prevalence Analysis of Non-Small-Cell and Small-Cell Lung Cancer Using Administrative Data

Treatment of lung cancer depends on the stage of the tumor and the histological type. In recent years, the histological confirmation of lung non-small-cell lung cancer has become crucial since the availability of selective target therapeutic approaches. The aim of the study was to develop a validated procedure to estimate the incidence and prevalence of non-small-cell and small-cell lung cancer from healthcare administrative data. A latent class model for categorical variables was applied. The following observed variables were included in the analysis: ICD-9-CM codes in the Hospital Discharge Registry, ATC codes of medications dispensed present in the Drugs Prescriptions Registry, and the procedure codes in the Outpatient Registry. The proportion of non-small-cell lung cancer diagnoses was estimated to be 85% of the total number of lung cancer on the cohort of incident cases and 89% on the cohort of prevalent cases. External validation on a cohort of 107 patients with a lung cancer diagnosis and histological confirmation showed a sensitivity of 95.6% (95%CI: 89–98.8%) and specificity of 94.1% (95%CI: 71.3–99.9%). The procedure is an easy-to-use tool to design subpopulation-based studies on lung cancer and to better plan resource allocation, which is important since the introduction of new targeted therapies in non-small-cell lung carcinoma.